Paulo Tarso Sanches de Oliveira

Perdas de solo e de água e infiltração de água em latossolo vermelho sob sistemas de manejo

Os sistemas de manejo do solo alteram o microrrelevo e a cobertura por residuos vegetais, influenciando a perda de solo e de agua. Assim, os objetivos deste estudo foram avaliar as perdas de solo e de agua e estimar a taxa de infiltracao estavel de agua no solo (TIE) em diferentes sistemas de manejo, sob chuva simulada. As avaliacoes de campo foram conduzidas sobre residuos vegetais, apos a colheita da cultura da soja (Glycine max L. Merril). Estudaram-se tres sistemas de manejo do solo: semeadura direta, preparo com grade aradora e com escarificador associados a tres niveis de cobertura do solo com residuo vegetal: 0,0; 2,0; e 4,0 Mg ha-1. Para caracterizar a area experimental foram feitas analises de densidade do solo, macroporosidade, estabilidade de agregados, umidade inicial do solo, percentual de cobertura e rugosidade superficial do solo. Por meio do uso do simulador de chuvas portatil, as parcelas receberam aplicacao de precipitacoes de 60 mm h-1. Os tratamentos foram dispostos segundo o delineamento inteiramente casualizado, arranjados em esquema fatorial 3 x 3, com tres repeticoes. As perdas de solo variaram de 1,40 a 116,30 x 10-3 Mg ha-1 h-1, enquanto as de agua, de 1,60 a 106,94 m3 ha-1 h-1. Os valores da TIE apresentaram variacao entre 23 e 52 mm h-1. Os tratamentos sob semeadura direta sem cobertura do solo e sob preparo com grade aradora apresentaram maiores perdas de solo e de agua e valores mais baixos de TIE.

Trends in water balance components across the Brazilian Cerrado

We assess the water balance of the Brazilian Cerrado based on remotely sensed estimates of precipitation (TRMM), evapotranspiration (MOD16), and terrestrial water storage (GRACE) for the period from 2003 to 2010. Uncertainties for each remotely sensed data set were computed, the budget closure was evaluated using measured discharge data for the three largest river basins in the Cerrado, and the Mann-Kendall test was used to evaluate temporal trends in the water balance components and measured river discharge. The results indicate an overestimation of discharge data, due mainly to the overestimation of rainfall by TRMM version 6. However, better results were obtained when the new release of TRMM 3B42 v7 was used instead. Our results suggest that there have been (a) significant increases in average annual evapotranspiration over the entire Cerrado of 51 ± 15 mm yr−1, (b) terrestrial water storage increases of 11 ± 6 mm yr−1 in the northeast region of the Brazilian Cerrado, and (c) runoff decreases of 72 ± 11 mm yr−1 in isolated spots and in the western part of the State of Mato Grosso. Although complete water budget closure from remote sensing remains a significant challenge due to uncertainties in the data, it provides a useful way to evaluate trends in major water balance components over large regions, identify dry periods, and assess changes in water balance due to land cover and land use change.

Global rainfall erosivity assessment based on high-temporal resolution rainfall records

The exposure of the Earth’s surface to the energetic input of rainfall is one of the key factors controlling water erosion. While water erosion is identified as the most serious cause of soil degradation globally, global patterns of rainfall erosivity remain poorly quantified and estimates have large uncertainties. This hampers the implementation of effective soil degradation mitigation and restoration strategies. Quantifying rainfall erosivity is challenging as it requires high temporal resolution(<30 min) and high fidelity rainfall recordings. We present the results of an extensive global data collection effort whereby we estimated rainfall erosivity for 3,625 stations covering 63 countries. This first ever Global Rainfall Erosivity Database was used to develop a global erosivity map at 30 arc-seconds(~1 km) based on a Gaussian Process Regression(GPR). Globally, the mean rainfall erosivity was estimated to be 2,190 MJ mm ha−1 h−1 yr−1, with the highest values in South America and the Caribbean countries, Central east Africa and South east Asia. The lowest values are mainly found in Canada, the Russian Federation, Northern Europe, Northern Africa and the Middle East. The tropical climate zone has the highest mean rainfall erosivity followed by the temperate whereas the lowest mean was estimated in the cold climate zone.

Variabilidade espacial do potencial erosivo das chuvas no estado de Mato Grosso do Sul

Information about rainfall erosivity is important during soil and water conservation planning. Thus, the spatial variability of rainfall erosivity of the state Mato Grosso do Sul was analyzed using ordinary kriging interpolation. For this, three pluviograph stations were used to obtain the regression equations between the erosivity index and the rainfall coefficient EI30. The equations obtained were applied to 109 pluviometric stations, resulting in EI30 values. These values were analyzed from geostatistical technique, which can be divided into: descriptive statistics, adjust to semivariogram, cross-validation process and implementation of ordinary kriging to generate the erosivity map.Highest erosivity values were found in central and northeast regions of the State, while the lowest values were observed in the southern region. In addition, high annual precipitation values not necessarily produce higher erosivity values.

Caracterização morfométrica de bacias hidrográficas através de dados SRTM

Visa-se, neste trabalho, avaliar os dados Shuttle Radar Topography Mission (SRTM) na caracterizacao morfometrica de bacias hidrograficas, atraves da comparacao das caracteristicas obtidas a partir de dados SRTM e de cartas topograficas, processados em Sistema de Informacao Geografica (SIG). O estudo foi realizado tomando-se por base a bacia hidrografica do Ribeirao Salobra, com area aproximada de 540 km2. A diferenca percentual obtida nos dados morfometricos entre os metodos estudados foi inferior a 11%, exceto no indice de circularidade (22%) e declividade media (55%). A utilizacao de dados SRTM em ambiente SIG permite a caracterizacao morfometrica de bacias hidrograficas, podendo auxiliar a gestao e o gerenciamento dos recursos hidricos, mostrando-se uma alternativa pratica e viavel ao minimizar custos e tempo na execucao dos trabalhos.

Performance evaluation of rainfall estimates by TRMM Multi‐satellite Precipitation Analysis 3B42V6 and V7 over Brazil

Time series precipitation data generated by the Tropical Rainfall Measuring Mission (TRMM) have been used as a possible solution for providing rainfall information for ungauged regions. We evaluated the quality of TRMM Multi-satellite Precipitation Analysis (TMPA) Version 6 (3B42V6) and Version 7 (3B42V7) products on a daily and monthly basis for a 14 year time series by comparing with gridded ground-based rainfall data from ~3625 rain gauges distributed throughout Brazil. The results show that daily estimates are inaccurate for both Versions 6 and 7 (the refined index of agreement, dr, was less than 0.6 in most of the analyzed pixels). In general, both versions perform well on monthly basis (dr > 0.75), but no significant improvement between them could be identified with the exception of local areas. TMPA performed poorly in the northwest region, where rainfall depths are higher in Brazil; however, the quality of the ground-based data is poor in this region because of low gauge density. Based on a seasonal analysis, we found that TMPA performed better during the dry seasons and that some improvements, although not significant, between successive versions took place over the northeast, southeast, and south regions. This study shows the value of remote sensing precipitation for providing reliable, spatiotemporally continuous precipitation at monthly timescales.

NDVI time series for monitoring RUSLE cover management factor in a tropical watershed

Land cover, an important factor for monitoring changes in land use and erosion risk, has been widely monitored and evaluated by vegetation indices. However, a study that associates normalized difference vegetation index (NDVI) time series to climate parameters to determine soil cover has yet to be conducted in the Atlantic Rainforest of Brazil, where anthropogenic activities have been carried out for centuries. The objective of this paper is to evaluate soil cover in a Brazilian Atlantic rainforest watershed using NDVI time series from Thematic Mapper (TM) Landsat 5 imagery from 1986 to 2009, and to introduce a new method for calculating the cover management factor (C-factor) of the Revised Universal Soil Loss Equation (RUSLE) model. Twenty-two TM Landsat 5 images were corrected for atmospheric effects using the 6S model, georeferenced using control points collected in the field and imported to a GIS database. Contour lines and elevation points were extracted from a 1:50,000-scale topographic map and used to construct a digital elevation model that defined watershed boundaries. NDVI and RUSLE C-factor values derived from this model were calculated within watershed limits with 1 km buffers. Rainfall data from a local weather station were used to verify NDVI and C-factor patterns in response to seasonal rainfall variations. Our proposed method produced realistic values for RUSLE C-factor using rescaled NDVIs, which highly correlated with other methods, and were applicable to tropical areas exhibiting high rainfall intensity. C-factor values were used to classify soil cover into different classes, which varied throughout the time-series period, and indicated that values attributed to each land cover cannot be fixed. Depending on seasonal rainfall distribution, low precipitation rates in the rainy season significantly affect the C-factor in the following year. In conclusion, NDVI time series obtained from satellite images, such as from Landsat 5, are useful for estimating the cover management factor and monitoring watershed erosion. These estimates may replace table values developed for specific land covers, thereby avoiding the cumbersome field measurements of these factors. The method proposed is recommended for estimating the RUSLE C-factor in tropical areas with high rainfall intensity.

Estimativa da evapotranspiração de referência através de redes neurais artificiais

The estimation of evapotranspiration by indirect methods provides synthetic data for planning irrigation systems and application on meteorological and hydrological models, both useful in watershed management. The objective of this study was to develop an Artificial Neural Network (ANN) to estimate the reference evapotranspiration (Eto) based on daily air temperature data. The ANN model of Feedforward Multilayer Perceptron type, was trained using as a reference the daily Eto obtained by the Penman-Monteith method. In the intermediate and output layers were used activation functions like tan-sigmoid and linear, respectively. Eto values generated by ANN were compared with those obtained by the methods of Blanney-Criddle and Hargreaves considering the months of the four seasons. Comparing to the other analyzed methods, the results obtained from the ANN were closer to the standard Penman-Monteith method. Thus, the performance of the developed ANN was satisfactory, and the ANN model can be considered as one indirect method for estimating evapotranspiration and allows a cost reduction on data acquisition to estimate this variable.

Curve number estimation from Brazilian Cerrado rainfall and runoff data

The Curve Number (CN) method has been widely used to estimate runoff from rainfall events in Brazil; however, CN values for use in the Brazilian savanna (Cerrado) are poorly documented. In this study we used experimental plots to measure natural rain-fall-driven rates of runoff under undisturbed Cerrado and under the main crops found in this region, and derive associated CN values from the measured data using five different statistical methods. Curve numbers obtained from the standard USDA Natural Resources Conservation Service (NRCS) table were suitable to estimate runoff for bare soil, soybeans (Glycine max [L.] Merr.), and sugarcane (Saccharum L.). However, CN values obtained from measured rainfall-runoff data (CN calibrated) provided better runoff estimates than the CN values from the standard table. The best CN values for the bare soil (hydrologic soil group B), soybeans, and sugarcane were 81.2 (78.5 to 83.9), 78.7 (75.9 to 81.5), and 70.2 (67.8 to 72.6). The CN method was not adequate to estimate runoff for the undisturbed Cerrado, bare soil (hydrologic soil group A), pasture, and millet (Pennisetum glaucum).

Water infiltration in an ultisol after cultivation of common bean

Water infiltration in the soil is an important hydrological process that occurs at the interface of the soil-atmosphere system; thus, the soil management practice used has a strong influence on this process. The aim of this study was to evaluate water infiltration in the soil and compare equations for estimating the water infiltration rate in an Ultisol after harvesting common bean (Phaseolus vulgaris L.) under simulated rainfall. Field tests with a rainfall simulator were carried out in three soil management systems: minimum tillage (MT), conventional tillage (CT), and no tillage (NT). In NT, four levels of plant residue on the soil surface were evaluated: 0, 3, 6, and 9 t ha-1. The models of Kostiakov-Lewis, Horton, and Philip were used to estimate the infiltration rate. In the MT system, the final infiltration rate was 54 mm h-1, whereas in the CT and NT systems with up to 3 t ha-1 of plant residue on the soil surface, the rate was near 17 mm h-1. In addition, the results indicated that in the NT system the infiltration rate increased with plant residue coverage greater than 6 t ha-1, i.e., there was a positive correlation between plant cover and the water infiltration rate. The Horton model was the most suitable in representing the water infiltration process in the soil. Therefore, this model can be recommended for estimation of this variable regardless of the soil tillage system used.